Chen et al., 2017 - Google Patents

Prediction of apple internal qualities using hyperspectral imaging techniques

Chen et al., 2017

Document ID
13034475028917233333
Author
Chen X
Pang T
Tao H
Lin M
Yang H
Publication year
Publication venue
2017 International Conference on Advanced Mechatronic Systems (ICAMechS)

External Links

Snippet

Sugar content and firmness are significant internal properties and have important significance for quality grade and industry production. The hyperspectral imaging techniques was investigated for prediction of sugar content and firmness in apples. Mean …
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    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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    • G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light using near infra-red light
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    • G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light for analysing liquids, e.g. polluted water
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    • G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light using FTIR
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    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/65—Raman scattering
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